In order for unmanned vehicles to be truly autonomous, they must possess the ability to localize themselves when placed into an unknown environment and learn about the physical objects that surround them. For example, such vehicles learn information for high level applications such as mapping and vehicle localization as well as low level applications such as obstacle avoidance. Once a vehicle learns such information about the environment in which it is working, it is able to move about the environment freely and in an optimized pattern to fulfill its required tasks while staying out of harm's way. While various sensors have been developed for vehicles operating out of the water, the number of sensors available for use by underwater vehicles is limited.
For example, for vehicles working in outdoor environments, localization can be accomplished using satellite-based localization sensors (e.g., GPS sensors) capable of providing accuracy in the centimeter range. Also, laser-based range finders, including Light Detection and Ranging (LiDAR) sensors, are capable of providing vehicle information about the surrounding environment with millimeter accuracy. LiDAR sensors, however, have a high cost that is prohibitive for low budget applications and both LiDAR and satellite-based sensors do not function properly in indoor (i.e., enclosed) or underwater environments.
In underwater environments, the most common sensor technologies are based on acoustics. For example, Sound Navigation and Ranging (SONAR) can provide accurate sensor data for vehicles operating in large open water environments. However, in enclosed underwater spaces, such as swimming pools, acoustic based solutions such as SONAR are difficult to use due to the high number of multiple returns caused by reflections in the enclosed environment. As a result, some laser-based approaches have been proposed. For example, one approach includes a vehicle with a laser pointer projecting a single dot and a camera that visualizes the dot reflecting off of a wall of the enclosed space. Because of this design, such vehicles are only able to determine distance information related to a single location directly in front of the camera. Also, such designs rely heavily on calibration routines that map the laser pointer's location in an image frame with a distance. Another approach includes the use of a single laser line and camera to generate full 3D maps of underwater objects. However, it can be challenging to find the entire laser line in environments that are not extremely dark. As a result, this approach cannot be used in operating environments where large amounts of natural and artificial light may be present, such as swimming pool and spa environments.